Chatbot Sentiment Analysis Agent Transfer System
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Solution Overview
Problem
Automated chat bots lack the ability to understand human emotions, leading to user dissatisfaction in interactions.
Innovation Solution
A system that analyzes user input for sentiments and transfers the conversation to a suitable agent when certain sentiment thresholds are met, using a sentiment analyzer and agent selector to determine the need for agent intervention and select a skilled agent for topic relevance and emotional handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated chat bots are used to replace skilled personnel, then cost is reduced and productivity is improved, but user satisfaction deteriorates due to lack of emotional understanding
Solution Approach 1:
A sentiment analysis intermediary component is introduced between the automated chat bot and the user interaction flow. This intermediary analyzes user inputs for emotional content and determines when human agent intervention is necessary, allowing the system to maintain automated efficiency while providing human empathy when needed.
Solution Approach 2:
The system dynamically transitions between automated chat bot mode and human agent mode based on real-time sentiment analysis. When user sentiment indicates distress or complex emotional needs, the system dynamically routes the conversation to a human agent, creating a flexible hybrid service model that adapts to user needs.
2Reliability
If sentiment analysis and agent transfer capabilities are added to the chat system, then user satisfaction is improved, but device complexity increases
Solution Approach 1:
The chat system is segmented into distinct functional modules: an automated chat bot handler, a sentiment analysis component, and an agent routing system. Each module performs a specific function, making the overall complex system manageable through clear separation of concerns and independent component development.
Solution Approach 2:
The sentiment analysis component serves multiple functions: it detects user emotions, determines transfer necessity, and provides context for agent routing. This multi-functional approach reduces overall system complexity by consolidating multiple capabilities into a single versatile component rather than requiring separate systems for each function.
Data Source
AI summary
Embodiments of the present invention disclose a method, computer program product, and system for an automated chat bot conversation session and an agent transfer system for the conversation session. The computer receives a user input from a user in an automated chat bot conversation session. The computer analyzes the user input for at least one sentiment, wherein an at least one analysis result is a value assigned to the at least one sentiment contained within the user input. The computer compares the at least one analysis result to a threshold value to determine if the user should be transferred from the automated chat bot conversation session to a conversation session with a suitable agent. The computer then transfers the user to the conversation session with the suitable agent.